Nonparametric regression with multiple thresholds: Estimation and inference
| Autor: | Jau-er Chen, Yan-Yu Chiou, Mei-Yuan Chen |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Economics and Econometrics
Sequential estimation General Economics (econ.GN) Threshold limit value Applied Mathematics 05 social sciences Monte Carlo method Estimator Asymptotic distribution Inference Quantitative Finance - Economics 01 natural sciences Nonparametric regression FOS: Economics and business 010104 statistics & probability 0502 economics and business Statistics 0101 mathematics 050205 econometrics Mathematics Variable (mathematics) |
| Zdroj: | Journal of Econometrics. 206:472-514 |
| ISSN: | 0304-4076 |
| DOI: | 10.1016/j.jeconom.2018.06.011 |
| Popis: | This paper examines nonparametric regression with an exogenous threshold variable, allowing for an unknown number of thresholds. Given the number of thresholds and corresponding threshold values, we first establish the asymptotic properties of the local constant estimator for a nonparametric regression with multiple thresholds. However, the number of thresholds and corresponding threshold values are typically unknown in practice. We then use our testing procedure to determine the unknown number of thresholds and derive the limiting distribution of the proposed test. The Monte Carlo simulation results indicate the adequacy of the modified test and accuracy of the sequential estimation of the threshold values. We apply our testing procedure to an empirical study of the 401(k) retirement savings plan with income thresholds. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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